A Compact Representation for Minimizers of k-Submodular Functions (Extended Abstract). - Hiroshi Hirai 001; Taihei Oki (ISCO, 2016)

Multi-dimensional Graph Fourier Transform. - Takashi Kurokawa; Taihei Oki; Hiromichi Nagao (CoRR, 2017)

A compact representation for minimizers of k-submodular functions. - Hiroshi Hirai 001; Taihei Oki (J. Comb. Optim., 2018)

Improved Structural Methods for Nonlinear Differential-Algebraic Equations via Combinatorial Relaxation. - Taihei Oki (ISSAC, 2019)

Computing the Maximum Degree of Minors in Skew Polynomial Matrices. - Taihei Oki (CoRR, 2019)

A Generalized Matrix-Tree Theorem for Pfaffian Pairs. - Taihei Oki (CoRR, 2019)

Index Reduction for Differential-algebraic Equations with Mixed Matrices. - Satoru Iwata 001; Taihei Oki; Mizuyo Takamatsu (J. ACM, 2019)

On Solving (Non)commutative Weighted Edmonds' Problem. - Taihei Oki (ICALP, 2020)

Dynamic Programming Approach to the Generalized Minimum Manhattan Network Problem. - Yuya Masumura; Taihei Oki; Yutaro Yamaguchi 001 (Algorithmica, 2021)

Lazy and Fast Greedy MAP Inference for Determinantal Point Process. - Shinichi Hemmi; Taihei Oki; Shinsaku Sakaue; Kaito Fujii; Satoru Iwata 001 (NeurIPS, 2022)

Sample Complexity of Learning Heuristic Functions for Greedy-Best-First and A* Search. - Shinsaku Sakaue; Taihei Oki (NeurIPS, 2022)

Discrete-Convex-Analysis-Based Framework for Warm-Starting Algorithms with Predictions. - Shinsaku Sakaue; Taihei Oki (NeurIPS, 2022)

Pfaffian Pairs and Parities: Counting on Linear Matroid Intersection and Parity Problems. - Kazuki Matoya; Taihei Oki (SIAM J. Discret. Math., 2022)

Improved Generalization Bound and Learning of Sparsity Patterns for Data-Driven Low-Rank Approximation. - Shinsaku Sakaue; Taihei Oki (AISTATS, 2023)

Rethinking Warm-Starts with Predictions: Learning Predictions Close to Sets of Optimal Solutions for Faster L-/L♮-Convex Function Minimization. - Shinsaku Sakaue; Taihei Oki (ICML, 2023)

Faster Discrete Convex Function Minimization with Predictions: The M-Convex Case. - Taihei Oki; Shinsaku Sakaue (NeurIPS, 2023)

Algebraic Algorithms for Fractional Linear Matroid Parity via Non-commutative Rank. - Taihei Oki; Tasuku Soma (SODA, 2023)

Data-Driven Projection for Reducing Dimensionality of Linear Programs: Generalization Bound and Learning Methods. - Shinsaku Sakaue; Taihei Oki (CoRR, 2023)

Algebraic combinatorial optimization on the degree of determinants of noncommutative symbolic matrices. - Hiroshi Hirai 001; Yuni Iwamasa; Taihei Oki; Tasuku Soma (CoRR, 2023)

Rate Constant Matrix Contraction Method for Stiff Master Equations with Detailed Balance. - Satoru Iwata 001; Taihei Oki; Shinsaku Sakaue (CoRR, 2023)

Computing valuations of the Dieudonné determinants. - Taihei Oki (J. Symb. Comput., 2023)

Online Structured Prediction with Fenchel-Young Losses and Improved Surrogate Regret for Online Multiclass Classification with Logistic Loss. - Shinsaku Sakaue; Han Bao 002; Taira Tsuchiya; Taihei Oki (COLT, 2024)

Problems on Group-Labeled Matroid Bases. - Florian Hörsch; András Imolay; Ryuhei Mizutani; Taihei Oki; Tamás Schwarcz (ICALP, 2024)

Structural Preprocessing Method for Nonlinear Differential-Algebraic Equations Using Linear Symbolic Matrices. - Taihei Oki; Yujin Song (ISSAC, 2024)

No-Regret M♮-Concave Function Maximization: Stochastic Bandit Algorithms and NP-Hardness of Adversarial Full-Information Setting. - Taihei Oki; Shinsaku Sakaue (NeurIPS, 2024)

Generalization Bound and Learning Methods for Data-Driven Projections in Linear Programming. - Shinsaku Sakaue; Taihei Oki (NeurIPS, 2024)

Position Fair Mechanisms Allocating Indivisible Goods. - Ryoga Mahara; Ryuhei Mizutani; Taihei Oki; Tomohiko Yokoyama (CoRR, 2024)

Fast and Numerically Stable Implementation of Rate Constant Matrix Contraction Method. - Shinichi Hemmi; Satoru Iwata 001; Taihei Oki (CoRR, 2024)

Fractional Linear Matroid Matching is in quasi-NC. - Rohit Gurjar; Taihei Oki; Roshan Raj (Electron. Colloquium Comput. Complex., 2024)

Towards the Proximity Conjecture on Group-Labeled Matroids. - Dániel Garamvölgyi; Ryuhei Mizutani; Taihei Oki; Tamás Schwarcz; Yutaro Yamaguchi 001 (ICALP, 2025)

Algorithmic Aspects of Semistability of Quiver Representations. - Yuni Iwamasa; Taihei Oki; Tasuku Soma (ICALP, 2025)

Mathematical Framework to Identify Optimal Molecule Based on Virtual Ligand Strategy. - Wataru Matsuoka; Ken Hirose; Ren Yamada; Taihei Oki; Satoru Iwata 001; Satoshi Maeda (J. Chem. Inf. Model., 2025)

Algebraic Algorithms for Fractional Linear Matroid Parity via Noncommutative Rank. - Taihei Oki; Tasuku Soma (SIAM J. Comput., 2025)

Online Inverse Linear Optimization: Improved Regret Bound, Robustness to Suboptimality, and Toward Tight Regret Analysis. - Shinsaku Sakaue; Taira Tsuchiya; Han Bao 002; Taihei Oki (CoRR, 2025)

Code for finding a non-SIBO matroid. - Dániel Garamvölgyi; Ryuhei Mizutani; Taihei Oki; Tamás Schwarcz; Yutaro Yamaguchi 001 (DROPS Artifacts, 2025)